The lower bound for dynamic parking prices to decrease congestion through CBD

Abstract

In this paper, some methods are developed to find the lower bound for dynamic parking prices (LPP) to manage the central business district (CBD) demand. Based on these prices, the private traffic flows of user equilibrium model or stochastic user equilibrium model converge to the predicted flow derived by system optimum model. To obtain LPP, a bi-level optimization model is studied for two types of CBD. In the first type which is referred by minor CBD, a new mathematical model is proposed to find LPP. In the second type, a general form of CBD namely major CBD is considered and a new algorithm entitled HABIB is proposed to estimate LPP. To decrease the computation time, a multi-layer perceptron neural network is used to learn solutions made by HABIB algorithm. It is shown that the accuracy of the proposed methods is acceptable. Also, the sensitivity analysis is done to illustrate the stability of the results in the absence of sufficient training data. Furthermore, the relations between LPP, public transportation costs and demands are investigated.